Integrated acoustic emission transducer apparatus and methods

ABSTRACT

Integrated acoustic emission transducer apparatus and methods are described. An example integrated external preamplifier device includes a data extractor, a process variable determiner, a status indication determiner, and a presentation device. The integrated external preamplifier device receives an acoustic emission signal generated via an acoustic emission sensor operatively coupled to the integrated external preamplifier device. The data extractor extracts signal data from the acoustic emission signal. The process variable determiner determines process variable data based on the extracted signal data. The process variable data includes at least one of flow rate data, flow capacity data, flow area data, flow velocity data, mass accumulation data, or volume accumulation data. The status indication determiner determines status indication data based on the process variable data. The presentation device presents at least one of the process variable data or the status indication data at the integrated external preamplifier device.

RELATED APPLICATIONS

This application arises from a continuation of U.S. patent applicationSer. No. 15/710,244, filed Sep. 20, 2017, entitled “Integrated AcousticEmission Transducer Apparatus and Methods,” the entirety of which ishereby incorporated herein by reference.

FIELD OF THE DISCLOSURE

This disclosure relates generally to acoustic emission apparatus andmethods and, more specifically, to integrated acoustic emissiontransducer apparatus and methods.

BACKGROUND

Acoustic emission sensors generate acoustic emission signals (e.g., anelectrical voltage signal) in response to acoustic emissions (e.g.,transient elastic waves) sensed, measured and/or detected via a sensingelement (e.g., one or more piezoelectric crystals) of the acousticemission sensor. Sources of acoustic emissions may include the formationand/or propagation of a material defect (e.g., a crack), slip and/ordislocation movements of a material, etc.

Conventional acoustic emission measurement and detection environmentsinclude an acoustic emission sensor, a preamplifier, a filter, anamplifier, an analog to digital converter, and a data processing device(e.g., a computer). In such conventional environments, the acousticemission signals are typically conditioned and/or modified via thepreamplifier, the filter, the amplifier, and the analog to digitalconverter, and then subsequently analyzed at the data processing deviceto detect and/or characterize acoustic emission events (e.g., formationand/or propagation of a material defect, determination of a leakagerate, etc.) associated with the acoustic emission signals.

SUMMARY

Integrated acoustic emission transducer apparatus and methods aredisclosed herein. In some disclosed examples, an apparatus comprises anintegrated external preamplifier device including a data extractor, aprocess variable determiner, a status indication determiner, and apresentation device. In some disclosed examples, the integrated externalpreamplifier device is to receive an acoustic emission signal generatedvia an acoustic emission sensor operatively coupled to the integratedexternal preamplifier device. In some disclosed examples, the dataextractor is to extract signal data from the acoustic emission signal.In some disclosed examples, the process variable determiner is todetermine process variable data based on the extracted signal data. Insome disclosed examples, the process variable data includes at least oneof flow rate data, flow capacity data, flow area data, flow velocitydata, mass accumulation data, or volume accumulation data. In somedisclosed examples, the status indication determiner is to determinestatus indication data based on the process variable data. In somedisclosed examples, the presentation device is to present at least oneof the process variable data or the status indication data at theintegrated external preamplifier device.

In some disclosed examples, a method comprises extracting signal data atan integrated external preamplifier device from an acoustic emissionsignal received at the integrated external preamplifier device. In somedisclosed examples, the acoustic emission signal is generated via anacoustic emission sensor operatively coupled to the integrated externalpreamplifier device. In some disclosed examples, the method furthercomprises determining process variable data at the integrated externalpreamplifier device based on the extracted signal data. In somedisclosed examples, the process variable data includes at least one offlow rate data, flow capacity data, flow area data, flow velocity data,mass accumulation data, or volume accumulation data. In some disclosedexamples, the method further comprises determining status indicationdata at the integrated external preamplifier device based on the processvariable data. In some disclosed examples, the method further comprisespresenting at least one of the process variable data or the statusindication data at the integrated external preamplifier device.

In some examples, a non-transitory computer readable storage mediumcomprising instructions is disclosed. In some disclosed examples, theinstructions, when executed, cause a processor to extract signal data atan integrated external preamplifier device from an acoustic emissionsignal received at the integrated external preamplifier device. In somedisclosed examples, the acoustic emission signal is generated via anacoustic emission sensor operatively coupled to the integrated externalpreamplifier device. In some disclosed examples, the instructions, whenexecuted, further cause the processor to determine process variable dataat the integrated external preamplifier device based on the extractedsignal data. In some disclosed examples, the process variable dataincludes at least one of flow rate data, flow capacity data, flow areadata, flow velocity data, mass accumulation data, or volume accumulationdata. In some disclosed examples, the instructions, when executed,further cause the processor to determine status indication data at theintegrated external preamplifier device based on the process variabledata. In some disclosed examples, the instructions, when executed,further cause the processor to present at least one of the processvariable data or the status indication data at the integrated externalpreamplifier device.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a known acoustic emission measurement anddetection environment.

FIG. 2 is a block diagram of a known implementation of the acousticemission sensor of FIG. 1 modified to include the preamplifier and thefilter of FIG. 1.

FIG. 3 is a block diagram of a known implementation of an externalpreamplifier device operatively coupled to the acoustic emission sensorof FIG. 1.

FIG. 4 is a block diagram of a first example integrated acousticemission transducer implemented via an example acoustic emission sensorconstructed in accordance with the teachings of this disclosure.

FIG. 5 is a block diagram of a second example integrated acousticemission transducer implemented via an example external preamplifierdevice constructed in accordance with the teachings of this disclosure.

FIG. 6 is a flowchart representative of an example method fordetermining, transmitting, and/or presenting process variable dataand/or status indication data via the first example integrated acousticemission transducer of FIG. 4.

FIG. 7 is a flowchart representative of an example method fordetermining, transmitting, and/or presenting process variable dataand/or status indication data via the second example integrated acousticemission transducer of FIG. 5.

FIG. 8 is a block diagram of an example processor platform capable ofexecuting instructions to implement the example method of FIG. 6 and thefirst example integrated acoustic emission transducer of FIG. 4.

FIG. 9 is a block diagram of an example processor platform capable ofexecuting instructions to implement the example method of FIG. 7 and thesecond example integrated acoustic emission transducer of FIG. 5.

Certain examples are shown in the above-identified figures and describedin detail below. In describing these examples, like or identicalreference numbers are used to identify the same or similar elements. Thefigures are not necessarily to scale and certain features and certainviews of the figures may be shown exaggerated in scale or in schematicfor clarity and/or conciseness.

DETAILED DESCRIPTION

Conventional acoustic emission measurement and detection environmentsinclude an acoustic emission sensor, a preamplifier, a filter, anamplifier, an analog to digital converter, and a data processing device(e.g., a computer). In such conventional environments, the acousticemission signals are typically conditioned and/or modified via thepreamplifier, the filter, the amplifier, and the analog to digitalconverter, and then subsequently analyzed at the data processing deviceto detect and/or characterize acoustic emission events (e.g., formationand/or propagation of a material defect, determination of a leakagerate, etc.) associated with the acoustic emission signals.

In some known acoustic emission measurement and detection environments,signal conditioning circuitry including the preamplifier, the filter,and the amplifier is included within a data acquisition device that alsoincludes the analog to digital converter. In other known acousticemission measurement and detection environments, the preamplifier andthe filter of the signal conditioning circuitry are integrated withinthe acoustic emission sensor, rather than being integrated within thedata acquisition device. In still other known acoustic emissionmeasurement and detection environments, the preamplifier and the filterof the signal conditioning circuitry are integrated within an externalpreamplifier device operatively located and/or positioned between theacoustic emission sensor and the data acquisition device, rather thanbeing integrated within the data acquisition device.

The above-described conventional acoustic emission measurement anddetection environments require high speed sampling (e.g., via the dataacquisition device) and extensive post-processing (e.g., via the dataprocessing device) to produce useful information regarding the integrityand/or health of the material(s) (e.g., process equipment) beingmonitored and/or evaluated. Examples of such useful information mayinclude determinations and/or estimations of leakage rate, flow rate,flow capacity, flow area, flow velocity, mass accumulation, and/orvolume accumulation associated with a process occurring within processequipment being monitored by the acoustic emission sensor, and mayfurther include determinations and/or estimations of valve health, valvewear, seal health, seal wear, and/or fugitive emissions associated withthe monitored process equipment.

The above-described conventional acoustic emission measurement anddetection environments fail to produce useful information (e.g., leakagerate data, flow rate data, valve health data, valve wear data, etc.) inreal time. Moreover, the aforementioned high speed sampling andextensive post-processing requirements of such conventional acousticemission measurement and detections systems necessitate theimplementation of high end data acquisition and data processingequipment, which increases the complexity and the cost of the acousticemission measurement and detection system. The implementation of suchhigh end equipment becomes technologically challenging in low powerand/or hazardous environments.

Unlike the above-described conventional acoustic emission measurementand detection environments, the integrated acoustic emission transducerapparatus and methods disclosed herein transduce, convert, and/orrestate one or more acoustic emission signal(s) generated by and/orreceived at the integrated acoustic emission transducer into usefulinformation (e.g., leakage rate, flow rate, valve health, valve wear,etc.) to be presented at the integrated acoustic emission transducer,and/or to be transmitted from the integrated acoustic emissiontransducer to an external device. Implementing the integrated acousticemission transducer apparatus and methods disclosed hereinadvantageously enables one or more acoustic emission signal(s) generatedby and/or received at the integrated acoustic emission transducer to betransduced, converted and/or restated into useful information at theintegrated acoustic emission transducer in real time without the needfor implementing high speed sampling and/or extensive, time-delayed,post-processing of the acoustic emission signal(s) via costly externaldata acquisition devices and/or external data processing devices. Beforedescribing the details of the disclosed integrated acoustic emissiontransducer apparatus and methods, a description of a known acousticemission measurement and detection environment is provided in connectionwith FIG. 1.

FIG. 1 is a block diagram of a known acoustic emission measurement anddetection environment 100. The acoustic emission measurement anddetection environment 100 of FIG. 1 includes an acoustic emission sensor102 and a data acquisition system 104. The data acquisition system 104of FIG. 1 includes a data acquisition device 106 and a data processingdevice 108 (e.g., a computer). The data acquisition device 106 includessignal conditioning circuitry 110 implemented as a preamplifier 112, afilter 114, and an amplifier 116. The data acquisition device 106 alsoincludes an analog signal detector 118 and an analog to digitalconverter 120. The data processing device 108 includes a processor 122and a memory 124. The processor 122 includes and/or implements an eventdetector 126. The memory 124 stores digital signal data 128, one or moreevent detection algorithm(s) 130, and event detection data 132. Theprocessor 122 and/or, more generally, the data processing device 108 ofFIG. 1 controls the operation of the data acquisition device 106 of FIG.1

The acoustic emission sensor 102 of FIG. 1 generates an acousticemission signal 134 in response to one or more acoustic emission(s)(e.g., transient elastic waves 136 of FIG. 1) sensed, measured and/ordetected via a sensing element (not shown) of the acoustic emissionsensor 102. The sensing element of the acoustic emission sensor 102 isimplemented as one or more piezoelectric crystal(s), as is known in theart. The acoustic emission(s) (e.g., the transient elastic waves 136)are sensed, measured and/or detected by the sensing element of theacoustic emission sensor 102 in response to the formation and/orpropagation of a defect (e.g. a crack 138 of FIG. 1) in a specimen 140of FIG. 1 to which the acoustic emission sensor 102 is coupled. Thespecimen 140 of FIG. 1 may be an item of process equipment (e.g., asegment of piping and/or conduit, a field device such as a valve, etc.).The acoustic emission signal 134 generated by the acoustic emissionsensor 102 is an analog signal. The generated acoustic emission signal134 is transmitted to and/or received at the data acquisition system 104of FIG. 1. More specifically, the acoustic emission signal 134 istransmitted to and/or received at the preamplifier 112 of the signalconditioning circuitry 110 of the data acquisition device 106 of thedata acquisition system 104 of FIG. 1.

The signal conditioning circuitry 110 of the data acquisition device 106of FIG. 1 conditions, alters and/or otherwise prepares the generatedacoustic emission signal 134 for further processing. The preamplifier112 of the signal conditioning circuitry 110 of FIG. 1 amplifies, boostsand/or strengthens the generated acoustic emission signal 134. Theamplified acoustic emission signal is transmitted from the preamplifier112 to the filter 114 of the signal conditioning circuitry 110 ofFIG. 1. The filter 114 filters the amplified acoustic emission signalbased on a non-selectable and/or non-programmable bandwidth associatedwith the filter 114. The filtered acoustic emission signal istransmitted from the filter 114 to the amplifier 116 of the signalconditioning circuitry 110 of FIG. 1. The amplifier 116 furtheramplifies, boosts and/or strengthens the filtered acoustic emissionsignal. The amplified acoustic emission signal is transmitted from theamplifier 116 to the analog signal detector 118 of the data acquisitiondevice 106 of FIG. 1.

In some known alternative implementations, the preamplifier 112, thefilter 114, and/or the amplifier 116 of the signal conditioningcircuitry 110 is/are located at (e.g., integrated within) the acousticemission sensor 102 of FIG. 1, and/or at an external preamplifier deviceoperatively located and/or positioned between the acoustic emissionsensor 102 of FIG. 1 and the data acquisition system 104 of FIG. 1. Forexample, FIG. 2 is a block diagram of a known implementation 200 of theacoustic emission sensor 102 of FIG. 1 modified to include thepreamplifier 112 and the filter 114 of FIG. 1. In the example of FIG. 2,the above-described operations and/or functions of the preamplifier 112and the filter 114 of FIG. 1 are performed at the acoustic emissionsensor 102 of FIG. 2, as opposed to being performed at the dataacquisition device 106 of the data acquisition system 104 of FIG. 1. Asanother example, FIG. 3 is a block diagram of a known implementation 300of an external preamplifier device 302 operatively located and/orpositioned between the acoustic emission sensor 102 of FIG. 1 and thedata acquisition system 104 of FIG. 1. In the example of FIG. 3, theabove-described operations and/or functions of the preamplifier 112 andthe filter 114 of FIG. 1 are performed at the external preamplifierdevice 302 of FIG. 3, as opposed to being performed at the dataacquisition device 106 of the data acquisition system 104 of FIG. 1.

Returning to the known acoustic emission measurement and detectionenvironment 100 of FIG. 1, the analog signal detector 118 of the dataacquisition device 106 detects the amplified signal transmitted from theamplifier 116 of the signal conditioning circuitry 110 as an analogwaveform. The analog to digital converter 120 of the data acquisitiondevice 106 converts the detected analog waveform into the digital signaldata 128. The digital signal data 128 is transmitted from the analog todigital converter 120 to the memory 124 of the data processing device108 of FIG. 1 where the digital signal data 128 is stored for furtherprocessing via the processor 122 of the data processing device 108 ofFIG. 1.

The processor 122 of the data processing device 108 of FIG. 1 implementsthe event detector 126 to detect the formation and/or propagation of oneor more defect(s) (e.g., the crack 138 of FIG. 1) in the specimen 140 ofFIG. 1. The event detector 126 detects one or more event(s) associatedwith the defect(s) (e.g., a leakage rate associated with the formationand/or propagation of the defect) based on the one or more eventdetection algorithm(s) 130 stored in the memory 124 and accessible tothe processor 122 and/or the event detector 126. The event detector 126and/or, more generally, the processor 122 of the data processing device108 of FIG. 1 transmits the event detection data 132 (e.g., datacorresponding to one or more event(s) detected by the event detector126) to the memory 124 of the data processing device 108 where the eventdetection data 132 is stored for further analysis and/or processing bythe processor 122.

FIG. 4 is a block diagram of a first example integrated acousticemission transducer 400 implemented via an example acoustic emissionsensor 402 constructed in accordance with the teachings of thisdisclosure. In the illustrated example of FIG. 4, the acoustic emissionsensor 402 includes an example sensing element 404, an examplepreamplifier 406, an example filter 408, an example data extractor 410,an example process variable determiner 412, an example status indicationdeterminer 414, an example network interface circuit 416, an examplepresentation device 418, an example data manager 420, and an examplememory 422. The network interface circuit 416 of FIG. 4 includes anexample transmitter 424 and an example receiver 426 respectively capableof communicating with one or more example external device(s) 428 (e.g.,a data processing device, such as a computer). The memory 422 of FIG. 4stores example extracted signal data 430, one or more example processvariable algorithm(s) 432, example process variable data 434, one ormore example status indication algorithm(s) 436, and example statusindication data 438.

In the illustrated example of FIG. 4, the sensing element 404, thepreamplifier 406, the filter 408, the data extractor 410, the processvariable determiner 412, the status indication determiner 414, thenetwork interface circuit 416, the presentation device 418, the datamanager 420, and the memory 422 are integrated within the acousticemission sensor 402 of the integrated acoustic emission transducer 400.In other examples, one or more of the filter 408, the data extractor410, the process variable determiner 412, the status indicationdeterminer 414, the network interface circuit 416, the presentationdevice 418, the data manager 420, and/or the memory 422 may beintegrated within the preamplifier 406 of the acoustic emission sensor402 of FIG. 4.

The acoustic emission sensor 402 of FIG. 4 generates an example acousticemission signal 440 in response to one or more acoustic emission(s)(e.g., transient elastic waves) sensed, measured and/or detected via thesensing element 404 of the acoustic emission sensor 402. In someexamples, the sensing element 404 of the acoustic emission sensor 402may be implemented as one or more piezoelectric crystal(s). In someexamples, the acoustic emission signal 440 generated by the acousticemission sensor 402 is an analog signal. In the illustrated example ofFIG. 4, the acoustic emission signal 440 generated by the acousticemission sensor 402 of FIG. 4 is transmitted to and/or received at thepreamplifier 406 of the acoustic emission sensor 402 of FIG. 4.

The preamplifier 406 of FIG. 4 amplifies, boosts and/or strengthens theacoustic emission signal 440. In the illustrated example of FIG. 4, thepreamplifier 406 amplifies, boosts and/or strengthens the acousticemission signal 440 prior to the acoustic emission signal 440 beingtransmitted to and/or received at the filter 408 of the acousticemission sensor 402 of FIG. 4. In other examples, the preamplifier 406of FIG. 4 may amplify, boost and/or strengthen the acoustic emissionsignal 440 after the acoustic emission signal 440 is filtered by thefilter 408 of the acoustic emission sensor 402 of FIG. 4. In theillustrated example of FIG. 4, the amplified acoustic emission signalgenerated by the preamplifier 406 is transmitted to and/or received atthe filter 408 of the acoustic emission sensor 402 of FIG. 4.

The filter 408 of FIG. 4 filters the acoustic emission signal 440. Thefilter 408 of FIG. 4 may be implemented as any type of filter including,for example, active, passive, superheterodyne, envelope detection,capacitor switching, field programmable gate array, finite impulseresponse, infinite impulse response, etc. In some examples, the filter408 of FIG. 4 may be implemented as a bandwidth-selectable filter asdisclosed in a U.S. patent application No. 15/710,270 entitled“Bandwidth-Selectable Acoustic Emission Apparatus and Methods forTransmitting Time-Averaged Signal Data”, filed on Sep. 20, 2017, theentirety of which is hereby incorporated by reference herein. In theillustrated example of FIG. 4, the conditioned (e.g., amplified andfiltered) acoustic emission signal generated by the filter 408 istransmitted to and/or received at the data extractor 410 of the acousticemission sensor 402 of FIG. 4.

The data extractor 410 of FIG. 4 extracts signal data (e.g., theextracted signal data 430 of FIG. 4) from the conditioned acousticemission signal. In some examples, the extracted signal data 430 of FIG.4 includes root mean square data associated with the conditionedacoustic emission signal. For example, the data extractor 410 mayextract and/or calculate root mean square data from the conditionedacoustic emission signal by squaring the values of the conditionedacoustic emission signal (e.g., squaring the function that defines thewaveform of the conditioned acoustic emission signal), by taking theaverage of the squared values (e.g., the average of the squaredfunction), and by taking the square root of the average values (e.g.,the square root of the average function). In other examples, theextracted signal data 430 of FIG. 4 includes average signal level dataassociated with the conditioned acoustic emission signal. For example,the data extractor 410 may additionally or alternatively extract and/orcalculate average signal level data from the conditioned acousticemission signal by taking the average signal values (e.g., the averageof the function that defines the waveform of the conditioned acousticemission signal) as a function of time. In still other examples, thedata extractor 410 may additionally or alternatively extract spectralcontent data associated with the acoustic emission signal, and/ortransient data associated with the acoustic emission signal. Theextracted signal data 430 of FIG. 4 may include such spectral contentdata and/or transient data.

The data extractor 410 of FIG. 4 transmits the extracted signal data 430to the memory 422 of the acoustic emission sensor 402 where theextracted signal data 430 is stored for further analysis and/orprocessing. The extracted signal data 430 stored in the memory 422 ofFIG. 4 is accessible to the data extractor 410, the process variabledeterminer 412, the status indication determiner 414, the networkinterface circuit 416, the presentation device 418, and/or the datamanager 420 of the acoustic emission sensor 402 of FIG. 4.

The process variable determiner 412 of FIG. 4 determines processvariable data (e.g., the process variable data 434 of FIG. 4) associatedwith the acoustic emission signal 440 based on the extracted signal data430 of FIG. 4. In some examples, the process variable determiner 412 ofFIG. 4 determines the process variable data 434 of FIG. 4 by applyingone or more of the process variable algorithm(s) 432 stored on thememory 422 to the extracted signal data 430 stored on the memory 422. Insuch examples, the one or more process variable algorithm(s) 432 and theextracted signal data 430 of FIG. 4 are accessible to the processvariable determiner 412 from the memory 422 of FIG. 4.

For example, based on the extracted signal data 430 of FIG. 4 and one ormore of the process variable algorithm(s) 432 of FIG. 4, the processvariable determiner 412 may determine and/or calculate leakage rate data(e.g., one type of the process variable data 434 of FIG. 4) associatedwith a process (e.g., a flow of fluid) occurring within processequipment (e.g., process piping, a valve, etc.) being monitored via theacoustic emissions sensor 402 of FIG. 4. In other examples, again basedon the extracted signal data 430 and one or more of the process variablealgorithm(s) 432, the process variable determiner 412 may additionallyor alternatively determine and/or calculate other types of processvariable data associated with the process occurring within the processequipment. For example, the process variable data 434 determined and/orcalculated by the process variable determiner 412 may additionally oralternatively include flow rate data, flow capacity data, flow areadata, flow velocity data, mass accumulation data, and/or volumeaccumulation data associated with the process occurring within theprocess equipment being monitored by the acoustic emission sensor 402 ofFIG. 4.

The process variable determiner 412 of FIG. 4 transmits the processvariable data 434 to the memory 422 of the acoustic emission sensor 402where the process variable data 434 is stored for further analysisand/or processing. The process variable data 434 stored in the memory422 of FIG. 4 is accessible to the process variable determiner 412, thestatus indication determiner 414, the network interface circuit 416, thepresentation device 418, and/or the data manager 420 of the acousticemission sensor 402 of FIG. 4.

The status indication determiner 414 of FIG. 4 determines statusindication data (e.g., the status indication data 438 of FIG. 4)associated with the acoustic emission signal 440 based on the processvariable data 434 and/or based on the extracted signal data 430 of FIG.4. In some examples, the status indication determiner 414 of FIG. 4determines the status indication data 438 of FIG. 4 by applying one ormore of the status indication algorithm(s) 436 stored on the memory 422to the process variable data 434 and/or to the extracted signal data 430stored on the memory 422. In such examples, the one or status indicationalgorithm(s) 436, the process variable data 434, and/or the extractedsignal data 430 of FIG. 4 are accessible to the status indicationdeterminer 414 from the memory 422 of FIG. 4.

For example, based on the process variable data 434 of FIG. 4 and/or theextracted signal data 430 of FIG. 4, and further based on one or more ofthe status indication algorithm(s) 436 of FIG. 4, the status indicationdeterminer 414 may determine and/or calculate valve health data (e.g.,one type of the status indication data 438 of FIG. 4) associated withprocess equipment (e.g., process piping, a valve, etc.) and/or a process(e.g., a flow of fluid) occurring within the process equipment, asmonitored via the acoustic emissions sensor 402 of FIG. 4. In someexamples, the valve health data may be expressed and/or represented as apercentage type of status indication associated with a total possiblevalve health (e.g., a textual, graphical and/or audible signal and/ormessage indicating that the valve health is eighty percent (80%) of atotal possible valve health). In other examples, the valve health datamay be expressed and/or represented as a pass/fail type of statusindication (e.g., a textual, graphical and/or audible signal and/ormessage indicating that the valve health satisfies (e.g., passes) avalve health threshold or does not satisfy (e.g., fails) the valvehealth threshold).

In other examples, again based on the process variable data 434 of FIG.4 and/or the extracted signal data 430 of FIG. 4, and further based onone or more of the status indication algorithm(s) 436 of FIG. 4, thestatus indication determiner 414 may additionally or alternativelydetermine and/or calculate other types of status indication dataassociated with the process equipment and/or the process occurringwithin the process equipment. For example, the status indication data438 determined and/or calculated by the status indication determiner 414may additionally or alternatively include valve wear data, seal healthdata, seal wear data, and/or fugitive emissions data associated with theprocess equipment and/or the process occurring within the processequipment, as monitored by the acoustic emission sensor 402 of FIG. 4.In such other examples, the different types of status indication datamay be expressed and/or represented in any form, including those formsdescribed above in relation to the valve heath data.

The status indication determiner 414 of FIG. 4 transmits the statusindication data 438 to the memory 422 of the acoustic emission sensor402 where the status indication data 438 is stored for further analysisand/or processing. The status indication data 438 stored in the memory422 of FIG. 4 is accessible to the status indication determiner 414, thenetwork interface circuit 416, the presentation device 418, and/or thedata manager 420 of the acoustic emission sensor 402 of FIG. 4.

The network interface circuit 416 of FIG. 4 may be implemented by anytype of interface standard, such as an Ethernet interface, a universalserial bus (USB), and/or a PCI express interface. The network interfacecircuit 416 of the illustrated example includes the transmitter 424 andthe receiver 426 of FIG. 4, and may further include a modem and/or anetwork interface card to facilitate exchange of data with the one ormore external device(s) 428 of FIG. 4 via a network. In some examples,the network over which the transmitter 424 and/or the receiver 426 ofthe network interface circuit 416 of FIG. 4 exchange(s) data with theone or more external device(s) 428 may be facilitated via 4-20 milliampwiring and/or via one or more communication protocol(s) including, forexample, Highway Addressable Remote Transducer (HART), FoundationFieldbus, Transmission Control Protocol/Internet Protocol (TCP/IP),Profinet, Modbus and/or Ethernet.

The transmitter 424 of the network interface circuit 416 of FIG. 4transmits data from the acoustic emission sensor 402 of FIG. 4 to one ormore of the external device(s) 428 of FIG. 4. For example, thetransmitter 424 may transmit some or all of the process variable data434 of FIG. 4, and/or some or all of the status indication data 438 ofFIG. 4 from the acoustic emission sensor 402 to one or more of theexternal device(s) 428. In some examples, the process variable data 434and/or the status indication data 438 of FIG. 4 transmitted by thetransmitter 424 may be the only data transmitted by the transmitter fromthe acoustic emission sensor 402 to the one or more external device(s)428 of FIG. 4. In some examples, the transmission of data via thetransmitter 424 of the network interface circuit 416 of the acousticemission sensor 402 of FIG. 4 is controlled and/or managed by the datamanager 420 of FIG. 4, as described below.

The presentation device 418 of FIG. 4 presents data in visual and/oraudible form at the acoustic emission sensor 402 of FIG. 4 including,for example, some or all of the process variable data 434 of FIG. 4,and/or some or all of the status indication data 438 of FIG. 4. Forexample, the presentation device 418 may be implemented as one or moreof a light emitting diode, a touchscreen, and/or a liquid crystaldisplay for presenting visual information, and/or a speaker forpresenting audible information. In some examples, the presentation ofdata via the presentation device 418 of the acoustic emission sensor 402of FIG. 4 is controlled and/or managed by the data manager 420 of FIG.4, as described below.

The data manager 420 of FIG. 4 controls and/or manages the transmissionof data via the transmitter 424 of FIG. 4. For example, the data manager420 may determine the conditions, circumstances, and/or timing underwhich the transmitter 424 is to transmit some or all of the processvariable data 434 and/or some or all of the status indication data 438of FIG. 4 from the acoustic emission sensor 402 of FIG. 4 to one or moreof the external device(s) 428 of FIG. 4. In some examples, the datamanager 420 may instruct and/or otherwise control the transmitter 424 totransmit some or all of the process variable data 434 and/or some or allof the status indication data 438 of FIG. 4 based on one or more controlsignal(s) communicated between the data manager 420 and the transmitter424.

The data manager 420 of FIG. 4 also controls and/or manages thepresentation of data at the presentation device 418 of the acousticemission sensor 402 of FIG. 4. For example, the data manager 420 maydetermine the conditions, circumstances, and/or timing under which thepresentation device 418 is to present some or all of the processvariable data 434 and/or some or all of the status indication data 438of FIG. 4. In some examples, the data manager 420 may instruct and/orotherwise control the presentation device 418 to present some or all ofthe process variable data 434 and/or some or all of the statusindication data 438 of FIG. 4 based on one or more control signal(s)communicated between the data manager 420 and the presentation device418.

The memory 422 of FIG. 4 stores the extracted signal data 430, the oneor more process variable algorithm(s) 432, the process variable data434, the one or more status indication algorithm(s) 436, and the statusindication data 438. The memory 422 of FIG. 4 may also store some or allof the data and/or data structures transmitted by the transmitter 424 ofFIG. 4 and/or received by the receiver 426 of FIG. 4. The memory 422 ofFIG. 4 may be implemented by any type(s) and/or any number(s) of storagedevice(s) such as a storage drive, a flash memory, a read-only memory(ROM), a random-access memory (RAM), a cache, and/or any other storagemedium in which data is stored for any duration (e.g., for extended timeperiods, permanently, brief instances, for temporarily buffering, and/orfor caching of the data). The data stored in the memory 422 of FIG. 4may be stored in any file and/or data structure format, organizationscheme, and/or arrangement. The memory 422 of FIG. 4 is accessible tothe data extractor 410, the process variable determiner 412, the statusindication determiner 414, the network interface circuit 416 (includingthe transmitter 424 and the receiver 426), the presentation device 418,the data manager 420, and/or, more generally, the acoustic emissionsensor 402 of FIG. 4.

While an example manner of implementing the integrated acoustic emissiontransducer 400 is illustrated in FIG. 4, one or more of the elements,processes and/or devices illustrated in FIG. 4 may be combined, divided,re-arranged, omitted, eliminated and/or implemented in any other way.Further, the example sensing element 404, the example preamplifier 406,the example filter 408, the example data extractor 410, the exampleprocess variable determiner 412, the example status indicationdeterminer 414, the example network interface circuit 416, the examplepresentation device 418, the example data manager 420, the examplememory 422 and/or, more generally the example acoustic emission sensor402 of the integrated acoustic emission transducer 400 of FIG. 4 may beimplemented by hardware, software, firmware and/or any combination ofhardware, software and/or firmware. Thus, for example, any of theexample sensing element 404, the example preamplifier 406, the examplefilter 408, the example data extractor 410, the example process variabledeterminer 412, the example status indication determiner 414, theexample network interface circuit 416, the example presentation device418, the example data manager 420, the example memory 422 and/or, moregenerally the example acoustic emission sensor 402 of the integratedacoustic emission transducer 400 of FIG. 4 could be implemented by oneor more analog or digital circuit(s), logic circuits, programmableprocessor(s), application specific integrated circuit(s) (ASIC(s)),programmable logic device(s) (PLD(s)) and/or field programmable logicdevice(s) (FPLD(s)). When reading any of the apparatus or system claimsof this patent to cover a purely software and/or firmwareimplementation, at least one of the example sensing element 404, theexample preamplifier 406, the example filter 408, the example dataextractor 410, the example process variable determiner 412, the examplestatus indication determiner 414, the example network interface circuit416, the example presentation device 418, the example data manager 420,the example memory 422 and/or, more generally the example acousticemission sensor 402 of the integrated acoustic emission transducer 400of FIG. 4 is/are hereby expressly defined to include a non-transitorycomputer readable storage device or storage disk such as a memory, adigital versatile disk (DVD), a compact disk (CD), a Blu-ray disk, etc.including the software and/or firmware. Further still, the exampleintegrated acoustic emission transducer 400 of FIG. 4 may include one ormore elements, processes and/or devices in addition to, or instead of,those illustrated in FIG. 4, and/or may include more than one of any orall of the illustrated elements, processes and devices.

FIG. 5 is a block diagram of a second example integrated acousticemission transducer 500 implemented via an example external preamplifierdevice 502 constructed in accordance with the teachings of thisdisclosure. In the illustrated example of FIG. 5, the externalpreamplifier device 502 is operatively coupled (e.g., in electricalcommunication with) an example acoustic emission sensor 504. Theacoustic emission sensor 504 of FIG. 5 includes the sensing element 404of the acoustic emission sensor 402 of FIG. 4 described above. With theexception of the sensing element 404 of FIG. 4 included within theacoustic emission sensor 504 of FIG. 5, the external preamplifier device502 of FIG. 5 includes all of the other components, structures and dataof the acoustic emission sensor 402 illustrated in FIG. 4 and describedabove. For example, as shown in FIG. 5, the external preamplifier device502 includes the preamplifier 406, the filter 408, the data extractor410, the process variable determiner 412, the status indicationdeterminer 414, the network interface circuit 416 (including thetransmitter 424 and the receiver 426), the presentation device 418, thedata manager 420, and the memory 422 (including the extracted signaldata 430, the one or more process variable algorithm(s) 432, the processvariable data 434, the one or more status indication algorithm(s) 436,and the status indication data 438) of the acoustic emission sensor 402of FIG. 4 described above.

In connection with the illustrated example of FIG. 5, the structure,function and/or operation of each of the preamplifier 406, the filter408, the data extractor 410, the process variable determiner 412, thestatus indication determiner 414, the network interface circuit 416(including the transmitter 424 and the receiver 426), the presentationdevice 418, the data manager 420, and the memory 422 (including theextracted signal data 430, the one or more process variable algorithm(s)432, the process variable data 434, the one or more status indicationalgorithm(s) 436, and the status indication data 438) of the externalpreamplifier device 502 of FIG. 5 is/are the same as the correspondingstructure, function and/or operation of the preamplifier 406, the filter408, the data extractor 410, the process variable determiner 412, thestatus indication determiner 414, the network interface circuit 416(including the transmitter 424 and the receiver 426), the presentationdevice 418, the data manager 420, and the memory 422 (including theextracted signal data 430, the one or more process variable algorithm(s)432, the process variable data 434, the one or more status indicationalgorithm(s) 436, and the status indication data 438) of the acousticemission sensor 402 of FIG. 4 described above. Thus, in the interest ofbrevity, the structure, function and/or operation of these components,structures and data of the external preamplifier device 502 of FIG. 5are not repeated herein.

In the illustrated example of FIG. 5, the preamplifier 406, the filter408, the data extractor 410, the process variable determiner 412, thestatus indication determiner 414, the network interface circuit 416, thepresentation device 418, the data manager 420, and the memory 422 areintegrated within the external preamplifier device 502 of the integratedacoustic emission transducer 500. In other examples, one or more of thefilter 408, the data extractor 410, the process variable determiner 412,the status indication determiner 414, the network interface circuit 416,the presentation device 418, the data manager 420, and/or the memory 422may be integrated within the preamplifier 406 of the externalpreamplifier device 502 of FIG. 5.

While an example manner of implementing the integrated acoustic emissiontransducer 500 is illustrated in FIG. 5, one or more of the elements,processes and/or devices illustrated in FIG. 5 may be combined, divided,re-arranged, omitted, eliminated and/or implemented in any other way.Further, the example preamplifier 406, the example filter 408, theexample data extractor 410, the example process variable determiner 412,the example status indication determiner 414, the example networkinterface circuit 416, the example presentation device 418, the exampledata manager 420, the example memory 422 and/or, more generally theexample external preamplifier device 502 of the integrated acousticemission transducer 500 of FIG. 5 may be implemented by hardware,software, firmware and/or any combination of hardware, software and/orfirmware. Thus, for example, any of the example preamplifier 406, theexample filter 408, the example data extractor 410, the example processvariable determiner 412, the example status indication determiner 414,the example network interface circuit 416, the example presentationdevice 418, the example data manager 420, the example memory 422 and/or,more generally the example external preamplifier device 502 of theintegrated acoustic emission transducer 500 of FIG. 5 could beimplemented by one or more analog or digital circuit(s), logic circuits,programmable processor(s), application specific integrated circuit(s)(ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)). When reading any of theapparatus or system claims of this patent to cover a purely softwareand/or firmware implementation, at least one of the example preamplifier406, the example filter 408, the example data extractor 410, the exampleprocess variable determiner 412, the example status indicationdeterminer 414, the example network interface circuit 416, the examplepresentation device 418, the example data manager 420, the examplememory 422 and/or, more generally the example external preamplifierdevice 502 of the integrated acoustic emission transducer 500 of FIG. 5is/are hereby expressly defined to include a non-transitory computerreadable storage device or storage disk such as a memory, a digitalversatile disk (DVD), a compact disk (CD), a Blu-ray disk, etc.including the software and/or firmware. Further still, the exampleintegrated acoustic emission transducer 500 of FIG. 5 may include one ormore elements, processes and/or devices in addition to, or instead of,those illustrated in FIG. 5, and/or may include more than one of any orall of the illustrated elements, processes and devices.

Flowcharts representative of example methods for determining,transmitting, and/or presenting process variable data and/or statusindication data via the first example integrated acoustic emissiontransducer 400 of FIG. 4 and the second example integrated acousticemission transducer 500 of FIG. 5 are respectively shown in FIGS. 6 and7. In these examples, the methods may be implemented using machinereadable instructions that comprise one or more program(s) for executionby one or more processor(s) such as the processor 802 shown in theexample processor platform 800 discussed below in connection with FIG.8, or the processor 902 shown in the example processor platform 900discussed below in connection with FIG. 9. The one or more program(s)may be embodied in software stored on a non-transitory computer readablestorage medium such as a CD-ROM, a floppy disk, a hard drive, a digitalversatile disk (DVD), a Blu-ray disk, or a memory associated with theprocessor 802 or the processor 902, but the entirety of any programand/or parts thereof could alternatively be executed by a device otherthan the processor 802 or the processor 902, and/or embodied in firmwareor dedicated hardware. Further, although the example program(s) is/aredescribed with reference to the flowcharts illustrated in FIGS. 6 and 7,many other methods of implementing the first example integrated acousticemission transducer 400 of FIG. 4 and/or the second example integratedacoustic emission transducer 500 of FIG. 5 may alternatively be used.For example, the order of execution of the blocks may be changed, and/orsome of the blocks described may be changed, eliminated, or combined.Additionally or alternatively, any or all of the blocks may beimplemented by one or more hardware circuits (e.g., discrete and/orintegrated analog and/or digital circuitry, a Field Programmable GateArray (FPGA), an Application Specific Integrated circuit (ASIC), acomparator, an operational-amplifier (op-amp), a logic circuit, etc.)structured to perform the corresponding operation without executingsoftware or firmware.

As mentioned above, the example methods of FIGS. 6 and 7 may beimplemented using coded instructions (e.g., computer and/or machinereadable instructions) stored on a non-transitory computer and/ormachine readable medium such as a hard disk drive, a flash memory, aread-only memory, a compact disk, a digital versatile disk, a cache, arandom-access memory and/or any other storage device or storage disk inwhich information is stored for any duration (e.g., for extended timeperiods, permanently, for brief instances, for temporarily buffering,and/or for caching of the information). As used herein, the termnon-transitory computer readable medium is expressly defined to includeany type of computer readable storage device and/or storage disk and toexclude propagating signals and to exclude transmission media.“Including” and “comprising” (and all forms and tenses thereof) are usedherein to be open ended terms. Thus, whenever a claim lists anythingfollowing any form of “include” or “comprise” (e.g., comprises,includes, comprising, including, etc.), it is to be understood thatadditional elements, terms, etc. may be present without falling outsidethe scope of the corresponding claim. As used herein, when the phrase“at least” is used as the transition term in a preamble of a claim, itis open-ended in the same manner as the term “comprising” and“including” are open ended.

FIG. 6 is a flowchart representative of an example method 600 fordetermining, transmitting, and/or presenting process variable dataand/or status indication data via the first example integrated acousticemission transducer 400 of FIG. 4. The example method 600 of FIG. 6begins when an acoustic emission sensor generates an acoustic emissionsignal (block 602). For example, the acoustic emission sensor 402 ofFIG. 4 may generate the acoustic emission signal 440 of FIG. 4 inresponse to one or more acoustic emission(s) (e.g., transient elasticwaves) sensed, measured and/or detected via the sensing element 404 ofthe acoustic emission sensor 402 of FIG. 4. Following block 602, controlof the example method 600 of FIG. 6 proceeds to block 604.

At block 604, signal conditioning circuitry of the acoustic emissionsensor conditions the acoustic emission signal (block 604). For example,the preamplifier 406 and/or the filter 408 of the acoustic emissionsensor 402 of FIG. 4 may condition the acoustic emission signal 440 ofFIG. 4 by respectively amplifying and/or filtering the acoustic emissionsignal 440. Following block 604, control of the example method 600 ofFIG. 6 proceeds to block 606.

At block 606, a data extractor of the acoustic emission sensor extractssignal data from the acoustic emission signal (block 606). For example,the data extractor 410 of FIG. 4 may extract and/or calculate root meansquare data from the acoustic emission signal 440 of FIG. 4 (e.g., asconditioned by the conditioning circuitry of the acoustic emissionsensor 402 of FIG. 4 at block 604 described above) by squaring thevalues of the acoustic emission signal 440 (e.g., squaring the functionthat defines the waveform of the acoustic emission signal 440), bytaking the average of the squared values (e.g., the average of thesquared function), and by taking the square root of the average values(e.g., the square root of the average function). As another example, thedata extractor 410 of FIG. 4 may additionally or alternatively extractand/or calculate average signal level data from the acoustic emissionsignal 440 of FIG. 4 by taking the average signal values (e.g., theaverage of the function that defines the waveform of the acousticemission signal 440) as a function of time. In still other examples, thedata extractor 410 of FIG. 4 may additionally or alternatively extractspectral content data associated with the acoustic emission signal 440of FIG. 4, and/or transient data associated with the acoustic emissionsignal 440 of FIG. 4. Following block 606, control of the example method600 of FIG. 6 proceeds to block 608.

At block 608, a process variable determiner of the acoustic emissionsensor determines process variable data associated with the acousticemission signal based on the extracted signal data (block 608). Forexample, the process variable determiner 412 of the acoustic emissionsensor 402 of FIG. 4 may implement one or more of the process variablealgorithm(s) 432 of FIG. 4 to determine the process variable data 434 ofFIG. 4 based on the extracted signal data 430 of FIG. 4. In someexamples, based on the extracted signal data 430 of FIG. 4 and one ormore of the process variable algorithm(s) 432 of FIG. 4, the processvariable determiner 412 of FIG. 4 may determine and/or calculate leakagerate data (e.g., one type of the process variable data 434 of FIG. 4)associated with a process (e.g., a flow of fluid) occurring withinprocess equipment (e.g., process piping, a valve, etc.) being monitoredvia the acoustic emissions sensor 402 of FIG. 4. In other examples,again based on the extracted signal data 430 and one or more of theprocess variable algorithm(s) 432, the process variable determiner 412may additionally or alternatively determine and/or calculate other typesof process variable data associated with the process occurring withinthe process equipment. For example, the process variable data 434 ofFIG. 4 determined and/or calculated by the process variable determiner412 of FIG. 4 may additionally or alternatively include flow rate data,flow capacity data, flow area data, flow velocity data, massaccumulation data, and/or volume accumulation data associated with theprocess occurring within the process equipment being monitored by theacoustic emission sensor 402 of FIG. 4. Following block 608, control ofthe example method 600 of FIG. 6 proceeds to block 610.

At block 610, a status indication determiner of the acoustic emissionsensor determines status indication data associated with the acousticemission signal based on the determined process variable data (block610). For example, the status indication determiner 414 of the acousticemission sensor 402 of FIG. 4 may implement one or more of the statusindication algorithm(s) 436 of FIG. 4 to determine the status indicationdata 438 of FIG. 4 based on the process variable data 434 of FIG. 4. Insome examples, based on the process variable data 434 of FIG. 4 and oneor more of the status indication algorithm(s) 436 of FIG. 4, the statusindication determiner 414 of FIG. 4 may determine and/or calculate valvehealth data (e.g., one type of the status indication data 438 of FIG. 4)associated with process equipment (e.g., process piping, a valve, etc.)and/or a process (e.g., a flow of fluid) occurring within the processequipment, as monitored via the acoustic emissions sensor 402 of FIG. 4.In some examples, the valve health data may be expressed and/orrepresented as a percentage type of status indication associated with atotal possible valve health (e.g., a textual, graphical and/or audiblesignal and/or message indicating that the valve health is eighty percent(80%) of a total possible valve health). In other examples, the valvehealth data may be expressed and/or represented as a pass/fail type ofstatus indication (e.g., a textual, graphical and/or audible signaland/or message indicating that the valve health satisfies (e.g., passes)a valve health threshold or does not satisfy (e.g., fails) the valvehealth threshold). In other examples, again based on the processvariable data 434 of FIG. 4 and one or more of the status indicationalgorithm(s) 436 of FIG. 4, the status indication determiner 414 of FIG.4 may additionally or alternatively determine and/or calculate othertypes of status indication data associated with the process equipmentand/or the process occurring within the process equipment. For example,the status indication data 438 determined and/or calculated by thestatus indication determiner 414 may additionally or alternativelyinclude valve wear data, seal health data, seal wear data, and/orfugitive emissions data associated with the process equipment and/or theprocess occurring within the process equipment, as monitored by theacoustic emission sensor 402 of FIG. 4. In such other examples, thedifferent types of status indication data may be expressed and/orrepresented in any form, including those forms described above inrelation to the valve heath data. Following block 610, control of theexample method 600 of FIG. 6 proceeds to block 612.

At block 612, a data manager of the acoustic emission sensor determineswhether to transmit data from the acoustic emission sensor to one ormore external device(s) (block 612). For example, the data manager 420of the acoustic emission sensor 402 of FIG. 4 may determine that theprocess variable data 434 and/or the status indication data 438 of FIG.4 is/are to be transmitted to one or more of the external device(s) 428of FIG. 4. If the data manager 420 determines at block 612 that data isto be transmitted from the acoustic emission sensor 402 to one or moreof the external device(s) 428, control of the example method 600 of FIG.6 proceeds to block 614. If the data manager 420 instead determines atblock 612 that data is not to be transmitted from the acoustic emissionsensor 402 to one or more of the external device(s) 428, control of theexample method 600 of FIG. 6 proceeds to block 616.

At block 614, a transmitter of the acoustic emission sensor transmitsprocess variable data and/or status indication data from the acousticemission sensor to one or more external device(s) (block 614). Forexample, the transmitter 424 of the acoustic emission sensor 402 of FIG.4 may transmit the process variable data 434 and/or the statusindication data 438 of FIG. 4 to one or more of the external device(s)428 of FIG. 4. Following block 614, control of the example method 600 ofFIG. 6 proceeds to block 616.

At block 616, the data manager of the acoustic emission sensordetermines whether to present data at a presentation device of theacoustic emission sensor (block 616). For example, the data manager 420of the acoustic emission sensor 402 of FIG. 4 may determine that theprocess variable data 434 and/or the status indication data 438 of FIG.4 is/are to be presented at the presentation device 418 of the acousticemission sensor 402 of FIG. 4. If the data manager 420 determines atblock 616 that data is to be presented at the presentation device 418 ofthe acoustic emission sensor 402, control of the example method 600 ofFIG. 6 proceeds to block 618. If the data manager 420 instead determinesat block 616 that data is not to be presented at the presentation device418 of the acoustic emission sensor 402, the example method 600 of FIG.6 ends.

At block 618, the presentation device of the acoustic emission sensorpresents process variable data and/or status indication data (block618). For example, the presentation device 418 of the acoustic emissionsensor 402 of FIG. 4 may present the process variable data 434 and/orthe status indication data 438 of FIG. 4. Following block 618, theexample method 600 of FIG. 6 ends.

FIG. 7 is a flowchart representative of an example method 700 fordetermining, transmitting, and/or presenting process variable dataand/or status indication data via the second example integrated acousticemission transducer 500 of FIG. 5. The example method 700 of FIG. 7begins when an external preamplifier device receives an acousticemission signal from an acoustic emission sensor (block 702). Forexample, the external preamplifier device 502 of FIG. 5 may receive theacoustic emission signal 440 of FIG. 5 from the acoustic emission sensor504 of FIG. 5. In some examples, the acoustic emission sensor 504 ofFIG. 5 may have generated the acoustic emission signal 440 of FIG. 5 inresponse to one or more acoustic emission(s) (e.g., transient elasticwaves) sensed, measured and/or detected via the sensing element 404 ofthe acoustic emission sensor 504 of FIG. 5. Following block 702, controlof the example method 700 of FIG. 7 proceeds to block 704.

At block 704, signal conditioning circuitry of the external preamplifierdevice conditions the acoustic emission signal (block 704). For example,the preamplifier 406 and/or the filter 408 of the external preamplifierdevice 502 of FIG. 5 may condition the acoustic emission signal 440 ofFIG. 5 by respectively amplifying and/or filtering the acoustic emissionsignal 440. Following block 704, control of the example method 700 ofFIG. 7 proceeds to block 706.

At block 706, a data extractor of the external preamplifier deviceextracts signal data from the acoustic emission signal (block 706). Forexample, the data extractor 410 of FIG. 5 may extract and/or calculateroot mean square data from the acoustic emission signal 440 of FIG. 5(e.g., as conditioned by the conditioning circuitry of the externalpreamplifier device 502 of FIG. 5 at block 704 described above) bysquaring the values of the acoustic emission signal 440 (e.g., squaringthe function that defines the waveform of the acoustic emission signal440), by taking the average of the squared values (e.g., the average ofthe squared function), and by taking the square root of the averagevalues (e.g., the square root of the average function). As anotherexample, the data extractor 410 of FIG. 4 may additionally oralternatively extract and/or calculate average signal level data fromthe acoustic emission signal 440 of FIG. 4 by taking the average signalvalues (e.g., the average of the function that defines the waveform ofthe acoustic emission signal 440) as a function of time. In still otherexamples, the data extractor 410 of FIG. 4 may additionally oralternatively extract spectral content data associated with the acousticemission signal 440 of FIG. 5, and/or transient data associated with theacoustic emission signal 440 of FIG. 5. Following block 706, control ofthe example method 700 of FIG. 7 proceeds to block 708.

At block 708, a process variable determiner of the external preamplifierdevice determines process variable data associated with the acousticemission signal based on the extracted signal data (block 708). Forexample, the process variable determiner 412 of the externalpreamplifier device 502 of FIG. 5 may implement one or more of theprocess variable algorithm(s) 432 of FIG. 5 to determine the processvariable data 434 of FIG. 5 based on the extracted signal data 430 ofFIG. 5. In some examples, based on the extracted signal data 430 of FIG.5 and one or more of the process variable algorithm(s) 432 of FIG. 5,the process variable determiner 412 of FIG. 5 may determine and/orcalculate leakage rate data (e.g., one type of the process variable data434 of FIG. 5) associated with a process (e.g., a flow of fluid)occurring within process equipment (e.g., process piping, a valve, etc.)being monitored via the acoustic emissions sensor 504 of FIG. 5. Inother examples, again based on the extracted signal data 430 and one ormore of the process variable algorithm(s) 432, the process variabledeterminer 412 may additionally or alternatively determine and/orcalculate other types of process variable data associated with theprocess occurring within the process equipment. For example, the processvariable data 434 of FIG. 5 determined and/or calculated by the processvariable determiner 412 of FIG. 5 may additionally or alternativelyinclude flow rate data, flow capacity data, flow area data, flowvelocity data, mass accumulation data, and/or volume accumulation dataassociated with the process occurring within the process equipment beingmonitored by the acoustic emission sensor 504 of FIG. 5. Following block708, control of the example method 700 of FIG. 7 proceeds to block 710.

At block 710, a status indication determiner of the externalpreamplifier device determines status indication data associated withthe acoustic emission signal based on the determined process variabledata (block 710). For example, the status indication determiner 414 ofthe external preamplifier device 502 of FIG. 5 may implement one or moreof the status indication algorithm(s) 436 of FIG. 5 to determine thestatus indication data 438 of FIG. 5 based on the process variable data434 of FIG. 5. In some examples, based on the process variable data 434of FIG. 5 and one or more of the status indication algorithm(s) 436 ofFIG. 5, the status indication determiner 414 of FIG. 5 may determineand/or calculate valve health data (e.g., one type of the statusindication data 438 of FIG. 5) associated with process equipment (e.g.,process piping, a valve, etc.) and/or a process (e.g., a flow of fluid)occurring within the process equipment, as monitored via the acousticemissions sensor 504 of FIG. 5. In some examples, the valve health datamay be expressed and/or represented as a percentage type of statusindication associated with a total possible valve health (e.g., atextual, graphical and/or audible signal and/or message indicating thatthe valve health is eighty percent (80%) of a total possible valvehealth). In other examples, the valve health data may be expressedand/or represented as a pass/fail type of status indication (e.g., atextual, graphical and/or audible signal and/or message indicating thatthe valve health satisfies (e.g., passes) a valve health threshold ordoes not satisfy (e.g., fails) the valve health threshold). In otherexamples, again based on the process variable data 434 of FIG. 5 and oneor more of the status indication algorithm(s) 436 of FIG. 5, the statusindication determiner 414 of FIG. 5 may additionally or alternativelydetermine and/or calculate other types of status indication dataassociated with the process equipment and/or the process occurringwithin the process equipment. For example, the status indication data438 determined and/or calculated by the status indication determiner 414may additionally or alternatively include valve wear data, seal healthdata, seal wear data, and/or fugitive emissions data associated with theprocess equipment and/or the process occurring within the processequipment, as monitored by the acoustic emission sensor 504 of FIG. 5.In such other examples, the different types of status indication datamay be expressed and/or represented in any form, including those formsdescribed above in relation to the valve heath data. Following block710, control of the example method 700 of FIG. 7 proceeds to block 712.

At block 712, a data manager of the external preamplifier devicedetermines whether to transmit data from the external preamplifierdevice to one or more external device(s) (block 712). For example, thedata manager 420 of the external preamplifier device 502 of FIG. 5 maydetermine that the process variable data 434 and/or the statusindication data 438 of FIG. 5 is/are to be transmitted to one or more ofthe external device(s) 428 of FIG. 5. If the data manager 420 determinesat block 712 that data is to be transmitted from the externalpreamplifier device 502 to one or more of the external device(s) 428,control of the example method 700 of FIG. 7 proceeds to block 714. Ifthe data manager 420 instead determines at block 712 that data is not tobe transmitted from the external preamplifier device 502 to one or moreof the external device(s) 428, control of the example method 700 of FIG.7 proceeds to block 716.

At block 714, a transmitter of the external preamplifier devicetransmits process variable data and/or status indication data from theexternal preamplifier device to one or more external device(s) (block714). For example, the transmitter 424 of the external preamplifierdevice 502 of FIG. 5 may transmit the process variable data 434 and/orthe status indication data 438 of FIG. 4 to one or more of the externaldevice(s) 428 of FIG. 5. Following block 714, control of the examplemethod 700 of FIG. 7 proceeds to block 716.

At block 716, the data manager of the external preamplifier devicedetermines whether to present data at a presentation device of theexternal preamplifier device (block 716). For example, the data manager420 of the external preamplifier device 502 of FIG. 5 may determine thatthe process variable data 434 and/or the status indication data 438 ofFIG. 5 is/are to be presented at the presentation device 418 of theexternal preamplifier device 502 of FIG. 5. If the data manager 420determines at block 716 that data is to be presented at the presentationdevice 418 of the external preamplifier device 502, control of theexample method 700 of FIG. 7 proceeds to block 718. If the data manager420 instead determines at block 716 that data is not to be presented atthe presentation device 418 of the external preamplifier device 502, theexample method 700 of FIG. 7 ends.

At block 718, the presentation device of the external preamplifierdevice presents process variable data and/or status indication data(block 718). For example, the presentation device 418 of the externalpreamplifier device 502 of FIG. 5 may present the process variable data434 and/or the status indication data 438 of FIG. 5. Following block718, the example method 700 of FIG. 7 ends.

FIG. 8 is a block diagram of an example processor platform 800 capableof executing instructions to implement the example method 600 of FIG. 6and the first example integrated acoustic emission transducer 400 ofFIG. 4. The processor platform 800 of the illustrated example includes aprocessor 802. The processor 802 of the illustrated example is hardware.For example, the processor 802 can be implemented by one or moreintegrated circuit(s), logic circuit(s), microprocessor(s) orcontroller(s) from any desired family or manufacturer. In the example ofFIG. 8, the processor 802 implements the example data extractor 410, theexample process variable determiner 412, the example status indicationdeterminer 414, and the example data manager 420 of FIG. 4. Theprocessor 802 of the illustrated example also includes a local memory804 (e.g., a cache).

The processor 802 of the illustrated example is in communication withone or more sensing element(s) 806 via a bus 808. In the example of FIG.8, the sensing element(s) 806 include the example sensing element 404 ofFIG. 4. The processor 802 of the illustrated example is also incommunication with one or more signal conditioner(s) 810 via the bus808. In the example of FIG. 8, the signal conditioner(s) 810 include theexample preamplifier 406 and the example filter 408 of FIG. 4. Theprocessor 802 of the illustrated example is also in communication withthe example presentation device 418 of FIG. 4.

The processor 802 of the illustrated example is also in communicationwith a main memory including a volatile memory 812 and a non-volatilememory 814 via the bus 808. The volatile memory 812 may be implementedby Synchronous Dynamic Random Access Memory (SDRAM), Dynamic RandomAccess Memory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM) and/orany other type of random access memory device. The non-volatile memory814 may be implemented by flash memory and/or any other desired type ofmemory device. Access to the volatile memory 812 and the non-volatilememory 814 is controlled by a memory controller. In the illustratedexample, the main memory 812, 814 includes the example memory 422 ofFIG. 4.

The processor platform 800 of the illustrated example also includes theexample network interface circuit 416 of FIG. 4. The network interfacecircuit 416 may be implemented by any type of interface standard, suchas an Ethernet interface, a universal serial bus (USB), and/or a PCIexpress interface. The network interface circuit 416 of the illustratedexample includes the example transmitter 424 and the example receiver426 of FIG. 4, and may further include a modem and/or a networkinterface card to facilitate exchange of data with the example externaldevice(s) 428 of FIG. 4 via a network 816. In some examples, the network816 may be facilitated via 4-20 milliamp wiring and/or via one or morecommunication protocol(s) including, for example, HART, FoundationFieldbus, TCP/IP, Profinet, Modbus and/or Ethernet.

Coded instructions 818 for implementing the example method 600 of FIG. 6may be stored in the local memory 804, in the volatile memory 812, inthe non-volatile memory 814, and/or on a removable tangible computerreadable storage medium such as a CD or DVD.

FIG. 9 is a block diagram of an example processor platform 900 capableof executing instructions to implement the example method 700 of FIG. 7and the second example integrated acoustic emission transducer 500 ofFIG. 5. The processor platform 900 of the illustrated example includes aprocessor 902. The processor 902 of the illustrated example is hardware.For example, the processor 902 can be implemented by one or moreintegrated circuit(s), logic circuit(s), microprocessor(s) orcontroller(s) from any desired family or manufacturer. In the example ofFIG. 9, the processor 902 implements the example data extractor 410, theexample process variable determiner 412, the example status indicationdeterminer 414, and the example data manager 420 of FIG. 5. Theprocessor 902 of the illustrated example also includes a local memory904 (e.g., a cache).

The processor 902 of the illustrated example is in communication withone or more signal conditioner(s) 906 via a bus 908. In the example ofFIG. 9, the signal conditioner(s) 906 include the example preamplifier406 and the example filter 408 of FIG. 5. The processor 902 of theillustrated example is also in communication with the examplepresentation device 418 of FIG. 5.

The processor 902 of the illustrated example is also in communicationwith a main memory including a volatile memory 910 and a non-volatilememory 912 via the bus 908. The volatile memory 910 may be implementedby Synchronous Dynamic Random Access Memory (SDRAM), Dynamic RandomAccess Memory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM) and/orany other type of random access memory device. The non-volatile memory912 may be implemented by flash memory and/or any other desired type ofmemory device. Access to the volatile memory 910 and the non-volatilememory 912 is controlled by a memory controller. In the illustratedexample, the main memory 910, 912 includes the example memory 422 ofFIG. 5.

The processor platform 900 of the illustrated example also includes theexample network interface circuit 416 of FIG. 5. The network interfacecircuit 416 may be implemented by any type of interface standard, suchas an Ethernet interface, a universal serial bus (USB), and/or a PCIexpress interface. The network interface circuit 416 of the illustratedexample includes the example transmitter 424 and the example receiver426 of FIG. 5, and may further include a modem and/or a networkinterface card to facilitate exchange of data with the example externaldevice(s) and/or the example acoustic emission sensor 504 of FIG. 5 viaa network 914. In some examples, the network 914 may be facilitated via4-20 milliamp wiring and/or via one or more communication protocol(s)including, for example, HART, Foundation Fieldbus, TCP/IP, Profinet,Modbus and/or Ethernet.

Coded instructions 916 for implementing the example method 700 of FIG. 7may be stored in the local memory 904, in the volatile memory 910, inthe non-volatile memory 912, and/or on a removable tangible computerreadable storage medium such as a CD or DVD.

From the foregoing, it will be appreciated that the disclosed integratedacoustic emission transducer apparatus and methods transduce, convert,and/or restate one or more acoustic emission signal(s) generated and/orreceived at the integrated acoustic emission transducer into usefulinformation (e.g., leakage rate, flow rate, valve health, valve wear,etc.) to be presented at the integrated acoustic emission transducer,and/or to be transmitted from the integrated acoustic emissiontransducer to an external device. Implementing the disclosed integratedacoustic emission transducer apparatus and methods advantageouslyenables one or more acoustic emission signal(s) generated by and/orreceived at the integrated acoustic emission transducer to betransduced, converted and/or restated into useful information at theintegrated acoustic emission transducer in real time without the needfor implementing high speed sampling and/or extensive, time-delayed,post-processing of the acoustic emission signal(s) via costly externaldata acquisition devices and/or external data processing devices.

In some disclosed examples, an apparatus comprises an acoustic emissionsensor including a data extractor and a process variable determiner. Insome disclosed examples, the acoustic emission sensor is to generate anacoustic emission signal. In some disclosed examples, the data extractoris to extract signal data from the acoustic emission signal. In somedisclosed examples, the process variable determiner is to determineprocess variable data based on the extracted signal data. In somedisclosed examples, the process variable data includes at least one ofleakage rate data, flow rate data, flow capacity data, flow area data,flow velocity data, mass accumulation data, or volume accumulation data.

In some disclosed examples of the apparatus, the extracted signal dataincludes at least one of root mean square data associated with theacoustic emission signal, average signal level data associated with theacoustic emission signal, spectral content data associated with theacoustic emission signal, or transient data associated with the acousticemission signal.

In some disclosed examples of the apparatus, the acoustic emissionsensor further includes a status indication determiner to determinestatus indication data based on the process variable data. In somedisclosed examples, the status indication data includes at least one ofvalve health data, valve wear data, seal health data, seal wear data, orfugitive emissions data. In some disclosed examples of the apparatus,the acoustic emission sensor further includes a transmitter to transmitat least one of the process variable data or the status indication datafrom the acoustic emission sensor to an external device. In somedisclosed examples of the apparatus, the acoustic emission sensorfurther includes a presentation device to present at least one of theprocess variable data or the status indication data at the acousticemission sensor.

In some disclosed examples of the apparatus, the acoustic emissionsensor further includes signal conditioning circuitry to condition theacoustic emission signal. In some disclosed examples, the signalconditioning circuitry includes a preamplifier. In some disclosedexamples of the apparatus, at least one of the data extractor or theprocess variable determiner is integrated within the preamplifier of theacoustic emission sensor.

In some disclosed examples, a method comprises extracting signal data atan acoustic emission sensor from an acoustic emission signal generatedvia the acoustic emission sensor. In some disclosed examples, the methodfurther comprises determining process variable data at the acousticemission sensor based on the extracted signal data. In some disclosedexamples, the process variable data includes at least one of leakagerate data, flow rate data, flow capacity data, flow area data, flowvelocity data, mass accumulation data, or volume accumulation data.

In some disclosed examples of the method, the extracted signal dataincludes at least one of root mean square data associated with theacoustic emission signal, average signal level data associated with theacoustic emission signal, spectral content data associated with theacoustic emission signal, or transient data associated with the acousticemission signal.

In some disclosed examples, the method further comprises determiningstatus indication data at the acoustic emission sensor based on theprocess variable data. In some disclosed examples, the status indicationdata includes at least one of valve health data, valve wear data, sealhealth data, seal wear data, or fugitive emissions data. In somedisclosed examples, the method further comprises transmitting at leastone of the process variable data or the status indication data from theacoustic emission sensor to an external device. In some disclosedexamples, the method further comprises presenting at least one of theprocess variable data or the status indication data at the acousticemission sensor via a presentation device of the acoustic emissionsensor.

In some examples, a non-transitory computer readable storage mediumcomprising instructions is disclosed. In some disclosed examples, theinstructions, when executed, cause a processor to extract signal data atan acoustic emission sensor from an acoustic emission signal generatedvia the acoustic emission sensor. In some disclosed examples, theinstructions, when executed, further cause the processor to determineprocess variable data at the acoustic emission sensor based on theextracted signal data. In some disclosed examples, the process variabledata includes at least one of leakage rate data, flow rate data, flowcapacity data, flow area data, flow velocity data, mass accumulationdata, or volume accumulation data.

In some disclosed examples of the non-transitory computer readablestorage medium, the extracted signal data includes at least one of rootmean square data associated with the acoustic emission signal, averagesignal level data associated with the acoustic emission signal, spectralcontent data associated with the acoustic emission signal, or transientdata associated with the acoustic emission signal.

In some disclosed examples of the non-transitory computer readablestorage medium, the instructions, when executed, further cause theprocessor to determine status indication data at the acoustic emissionsensor based on the process variable data. In some disclosed examples,the status indication data includes at least one of valve health data,valve wear data, seal health data, seal wear data, or fugitive emissionsdata. In some disclosed examples, the instructions, when executed,further cause the processor to instruct a transmitter of the acousticemission sensor to transmit at least one of the process variable data orthe status indication data from the acoustic emission sensor to anexternal device. In some disclosed examples, the instructions, whenexecuted, further cause the processor to instruct a presentation deviceof the acoustic emission sensor to present at least one of the processvariable data or the status indication data at the acoustic emissionsensor.

In some disclosed examples, an apparatus comprises an externalpreamplifier device including a data extractor and a process variabledeterminer. In some disclosed examples, the external preamplifier deviceis to receive an acoustic emission signal generated via an acousticemission sensor operatively coupled to the external preamplifier device.In some disclosed examples, the data extractor is to extract signal datafrom the acoustic emission signal. In some disclosed examples, theprocess variable determiner is to determine process variable data basedon the extracted signal data. In some disclosed examples, the processvariable data includes at least one of leakage rate data, flow ratedata, flow capacity data, flow area data, flow velocity data, massaccumulation data, or volume accumulation data.

In some disclosed examples of the apparatus, the extracted signal dataincludes at least one of root mean square data associated with theacoustic emission signal, average signal level data associated with theacoustic emission signal, spectral content data associated with theacoustic emission signal, or transient data associated with the acousticemission signal.

In some disclosed examples of the apparatus, the external preamplifierdevice further includes a status indication determiner to determinestatus indication data based on the process variable data. In somedisclosed examples, the status indication data includes at least one ofvalve health data, valve wear data, seal health data, seal wear data, orfugitive emissions data. In some disclosed examples of the apparatus,the external preamplifier device further includes a transmitter totransmit at least one of the process variable data or the statusindication data from the external preamplifier device to an externaldevice. In some disclosed examples of the apparatus, the externalpreamplifier device further includes a presentation device to present atleast one of the process variable data or the status indication data atthe external preamplifier device.

In some disclosed examples of the apparatus, the external preamplifierdevice further includes signal conditioning circuitry to condition theacoustic emission signal. In some disclosed examples, the signalconditioning circuitry includes a preamplifier. In some disclosedexamples of the apparatus, at least one of the data extractor or theprocess variable determiner is integrated within the preamplifier of theexternal preamplifier device.

In some disclosed examples, a method comprises extracting signal data atan external preamplifier device from an acoustic emission signalreceived at the external preamplifier device. In some disclosedexamples, the acoustic emission signal is generated via an acousticemission sensor operatively coupled to the external preamplifier device.In some disclosed examples, the method further comprises determiningprocess variable data at the external preamplifier device based on theextracted signal data. In some disclosed examples, the process variabledata includes at least one of leakage rate data, flow rate data, flowcapacity data, flow area data, flow velocity data, mass accumulationdata, or volume accumulation data.

In some disclosed examples of the method, the extracted signal dataincludes at least one of root mean square data associated with theacoustic emission signal, average signal level data associated with theacoustic emission signal, spectral content data associated with theacoustic emission signal, or transient data associated with the acousticemission signal.

In some disclosed examples, the method further comprises determiningstatus indication data at the external preamplifier device based on theprocess variable data. In some disclosed examples, the status indicationdata includes at least one of valve health data, valve wear data, sealhealth data, seal wear data, or fugitive emissions data. In somedisclosed examples, the method further comprises transmitting at leastone of the process variable data or the status indication data from theexternal preamplifier device to an external device. In some disclosedexamples, the method further comprises presenting at least one of theprocess variable data or the status indication data at the externalpreamplifier device via a presentation device of the externalpreamplifier device.

In some examples, a non-transitory computer readable storage mediumcomprising instructions is disclosed. In some disclosed examples, theinstructions, when executed, cause a processor to extract signal data atan external preamplifier device from an acoustic emission signalreceived at the external preamplifier device. In some disclosedexamples, the acoustic emission signal is generated via an acousticemission sensor operatively coupled to the external preamplifier device.In some disclosed examples, the instructions, when executed, furthercause the processor to determine process variable data at the externalpreamplifier device based on the extracted signal data. In somedisclosed examples, the process variable data includes at least one ofleakage rate data, flow rate data, flow capacity data, flow area data,flow velocity data, mass accumulation data, or volume accumulation data.

In some disclosed examples of the non-transitory computer readablestorage medium, the extracted signal data includes at least one of rootmean square data associated with the acoustic emission signal, averagesignal level data associated with the acoustic emission signal, spectralcontent data associated with the acoustic emission signal, or transientdata associated with the acoustic emission signal.

In some disclosed examples of the non-transitory computer readablestorage medium, the instructions, when executed, further cause theprocessor to determine status indication data at the externalpreamplifier device based on the process variable data. In somedisclosed examples, the status indication data includes at least one ofvalve health data, valve wear data, seal health data, seal wear data, orfugitive emissions data. In some disclosed examples, the instructions,when executed, further cause the processor to instruct a transmitter ofthe external preamplifier device to transmit at least one of the processvariable data or the status indication data from the externalpreamplifier device to an external device. In some disclosed examples,the instructions, when executed, further cause the processor to instructa presentation device of the external preamplifier device to present atleast one of the process variable data or the status indication data atthe external preamplifier device.

Although certain example methods, apparatus and articles of manufacturehave been disclosed herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

What is claimed is:
 1. An apparatus, comprising: an integrated externalpreamplifier device including a preamplifier, a data extractor, aprocess variable determiner, a status indication determiner, and apresentation device, the integrated external preamplifier device toreceive an acoustic emission signal generated via an acoustic emissionsensor operatively coupled to the integrated external preamplifierdevice, the data extractor to extract signal data from the acousticemission signal, the process variable determiner to determine processvariable data based on the extracted signal data, the process variabledata including at least one of flow rate data, flow capacity data, flowarea data, flow velocity data, mass accumulation data, or volumeaccumulation data, the status indication determiner to determine statusindication data based on the process variable data, the presentationdevice to present at least one of the process variable data or thestatus indication data at the integrated external preamplifier device.2. The apparatus of claim 1, wherein the extracted signal data includesat least one of root mean square data associated with the acousticemission signal, average signal level data associated with the acousticemission signal, spectral content data associated with the acousticemission signal, or transient data associated with the acoustic emissionsignal.
 3. The apparatus of claim 1, wherein the status indication dataincludes at least one of valve health data, valve wear data, or fugitiveemissions data.
 4. The apparatus of claim 1, wherein the integratedexternal preamplifier device further includes a transmitter to transmitat least one of the process variable data or the status indication datafrom the integrated external preamplifier device to another externaldevice.
 5. The apparatus of claim 1, wherein the integrated externalpreamplifier device further includes signal conditioning circuitry tocondition the acoustic emission signal, the signal conditioningcircuitry including the preamplifier.
 6. The apparatus of claim 5,wherein at least one of the data extractor or the process variabledeterminer is integrated within the preamplifier of the integratedexternal preamplifier device.
 7. The apparatus of claim 1, wherein thepresentation device is to present the at least one of the processvariable data or the status indication data at the integrated externalpreamplifier device in real time.
 8. The apparatus of claim 1, whereinthe presentation device is to present the status indication data at theintegrated external preamplifier device as a percentage type.
 9. Amethod, comprising: extracting signal data at an integrated externalpreamplifier device from an acoustic emission signal received at theintegrated external preamplifier device, the acoustic emission signalbeing generated via an acoustic emission sensor operatively coupled tothe integrated external preamplifier device; determining processvariable data at the integrated external preamplifier device based onthe extracted signal data, the process variable data including at leastone of flow rate data, flow capacity data, flow area data, flow velocitydata, mass accumulation data, or volume accumulation data; determiningstatus indication data at the integrated external preamplifier devicebased on the process variable data; and presenting at least one of theprocess variable data or the status indication data at the integratedexternal preamplifier device.
 10. The method of claim 9, wherein theextracted signal data includes at least one of root mean square dataassociated with the acoustic emission signal, average signal level dataassociated with the acoustic emission signal, spectral content dataassociated with the acoustic emission signal, or transient dataassociated with the acoustic emission signal.
 11. The method of claim 9,wherein the status indication data includes at least one of valve healthdata, valve wear data, or fugitive emissions data.
 12. The method ofclaim 9, further comprising transmitting at least one of the processvariable data or the status indication data from the integrated externalpreamplifier device to another external device.
 13. The method of claim9, wherein the presenting of the at least one of the process variabledata or the status indication data at the integrated externalpreamplifier device is in real time.
 14. The method of claim 9, whereinthe status indication data is presented at the integrated externalpreamplifier device as a percentage type.
 15. A non-transitory computerreadable storage medium comprising instructions that, when executed,cause a processor to at least: extract signal data at an integratedexternal preamplifier device from an acoustic emission signal receivedat the integrated external preamplifier device, the acoustic emissionsignal being generated via an acoustic emission sensor operativelycoupled to the integrated external preamplifier device; determineprocess variable data at the integrated external preamplifier devicebased on the extracted signal data, the process variable data includingat least one of flow rate data, flow capacity data, flow area data, flowvelocity data, mass accumulation data, or volume accumulation data;determine status indication data at the integrated external preamplifierdevice based on the process variable data; and present at least one ofthe process variable data or the status indication data at theintegrated external preamplifier device.
 16. The non-transitory computerreadable storage medium of claim 15, wherein the extracted signal dataincludes at least one of root mean square data associated with theacoustic emission signal, average signal level data associated with theacoustic emission signal, spectral content data associated with theacoustic emission signal, or transient data associated with the acousticemission signal.
 17. The non-transitory computer readable storage mediumof claim 15, wherein the status indication data includes at least one ofvalve health data, valve wear data, or fugitive emissions data.
 18. Thenon-transitory computer readable storage medium of claim 15, wherein theinstructions, when executed, further cause the processor to instruct atransmitter of the integrated external preamplifier device to transmitat least one of the process variable data or the status indication datafrom the integrated external preamplifier device to another externaldevice.
 19. The non-transitory computer readable storage medium of claim15, wherein the instructions, when executed, cause the processor topresent the at least one of the process variable data or the statusindication data at the integrated external preamplifier device in realtime.
 20. The non-transitory computer readable storage medium of claim15, wherein the status indication data is to be presented at theintegrated external preamplifier device as a percentage type.